Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study

Abstract

Aims Although highly heritable, the genetic etiology of calcific aortic stenosis (AS) remains incompletely understood. The aim of this study was to discover novel genetic contributors to AS and to integrate functional, expression, and cross-phenotype data to identify mechanisms of AS. Methods and results A genome-wide meta-analysis of 11.6 million variants in 10 cohorts involving 653 867 European ancestry participants (13 765 cases) was performed. Seventeen loci were associated with AS at P ≤ 5 × 10−8, of which 15 replicated in an independent cohort of 90 828 participants (7111 cases), including CELSR2–SORT1, NLRP6, and SMC2. A genetic risk score comprised of the index variants was associated with AS [odds ratio (OR) per standard deviation, 1.31; 95% confidence interval (CI), 1.26–1.35; P = 2.7 × 10−51] and aortic valve calcium (OR per standard deviation, 1.22; 95% CI, 1.08–1.37; P = 1.4 × 10−3), after adjustment for known risk factors. A phenome-wide association study indicated multiple associations with coronary artery disease, apolipoprotein B, and triglycerides. Mendelian randomization supported a causal role for apolipoprotein B-containing lipoprotein particles in AS (OR per g/L of apolipoprotein B, 3.85; 95% CI, 2.90–5.12; P = 2.1 × 10−20) and replicated previous findings of causality for lipoprotein(a) (OR per natural logarithm, 1.20; 95% CI, 1.17–1.23; P = 4.8 × 10−73) and body mass index (OR per kg/m2, 1.07; 95% CI, 1.05–1.9; P = 1.9 × 10−12). Colocalization analyses using the GTEx database identified a role for differential expression of the genes LPA, SORT1, ACTR2, NOTCH4, IL6R, and FADS. Conclusion Dyslipidemia, inflammation, calcification, and adiposity play important roles in the etiology of AS, implicating novel treatments and prevention strategies.

Novel Polygenic Risk Score and Established Clinical Risk Factors for Risk Estimation of Aortic Stenosis

“…Variants predisposing to higher lipoprotein(a) levels have been shown to be strongly associated with the risk of calcific aortic stenosis . This association may have potential therapeutic implications with the ongoing development of lipoprotein(a) modifying therapies, such as the antisense oligonucleotide pelacarsen and the small interfering RNA molecule olpasiran .…”

The influence of calcific aortic stenosis on atrioventricular conduction: a prospective observational study and Mendelian randomization

“…Additionally, the primary MR analysis was not restricted to strictly calcific AS, since some proportion of cases may have been a non-calcific phenotype. The majority of patients with AS do demonstrate a calcific phenotype, but nevertheless this limitation was formally addressed by performing supplementary analyses using SNPs that, in addition to being significant for AS at the conventional threshold of p < 5 x 10 -8 , were also associated with valvular calcification at p < 0.05 as per the original analysis 11 . The present analysis used a two-sample MR approach with overlapping samples, most notably with overlap from UK Biobank and deCODE for the analysis between AS and PR interval.…”

“…The exposure AS dataset was extracted from a genome wide association study (GWAS) meta-analysis of 10 cohorts which included 653,867 European participants (13,765 AS cases) 11 . As a sensitivity analysis, MR calculations were performed using a restricted subset of five SNPs that were also shown to be associated with aortic valve calcification (p<0.05) based on computed tomography assessment of 6,942 European participants 11 . The outcome PR interval data was from a GWAS meta-analysis of 40 cohorts including 271,570 European ancestry participants 12 .…”

Genetic Association of Serum Calcium, Phosphate, Vitamin D, Parathyroid Hormone, and FGF23 with the Risk of Aortic Stenosis

“…For the discovery analyses, summary genetic association data for CAVS was extracted from Freeze 9 of the FinnGen Consortium, involving 9,153 cases and 368,124 controls of European ancestry 29 . To validate our ndings through replication analysis, we used GWAS data for CAVS from a large-scale GWAS meta-analysis, comprising 13,765 cases and 640,102 controls from 10 European ancestry cohorts 30 . No duplication of cohort was found between these two GWAS datasets (Supplementary Table S2).…”

“…No duplication of cohort was found between these two GWAS datasets (Supplementary Table S2). Additional information regarding the diagnostic criteria, demographic factors, and quality control procedures can be found in the original GWAS study 29,30 .…”